Cloudera CCA-500 Exam Dumps 2021

NEW QUESTION 1
Which process instantiates user code, and executes map and reduce tasks on a cluster running MapReduce v2 (MRv2) on YARN?

• A. NodeManager
• B. ApplicationMaster
• C. TaskTracker
• D. JobTracker
• E. NameNode
• F. DataNode
• G. ResourceManager

Answer: A

NEW QUESTION 2
You decide to create a cluster which runs HDFS in High Availability mode with automatic failover, using Quorum Storage. What is the purpose of ZooKeeper in such a configuration?

• A. It only keeps track of which NameNode is Active at any given time
• B. It monitors an NFS mount point and reports if the mount point disappears
• C. It both keeps track of which NameNode is Active at any given time, and manages the Edits fil
• D. Which is a log of changes to the HDFS filesystem
• E. If only manages the Edits file, which is log of changes to the HDFS filesystem
• F. Clients connect to ZooKeeper to determine which NameNode is Active

Answer: A

Explanation: Reference: Reference:http://www.cloudera.com/content/cloudera-content/cloudera-docs/CDH4/latest/PDF/CDH4-High-Availability-Guide.pdf(page 15)

NEW QUESTION 3
You have installed a cluster HDFS and MapReduce version 2 (MRv2) on YARN. You have no dfs.hosts entry(ies) in your hdfs-site.xml configuration file. You configure a new worker node by setting fs.default.name in its configuration files to point to the NameNode on your cluster, and you start the DataNode daemon on that worker node. What do you have to do on the cluster to allow the worker node to join, and start sorting HDFS blocks?

• A. Without creating a dfs.hosts file or making any entries, run the commands hadoop.dfsadmin-refreshModes on the NameNode
• B. Restart the NameNode
• C. Creating a dfs.hosts file on the NameNode, add the worker Node’s name to it, then issue the command hadoop dfsadmin –refresh Nodes = on the Namenode
• D. Nothing; the worker node will automatically join the cluster when NameNode daemon is started

Answer: A

NEW QUESTION 4
You’re upgrading a Hadoop cluster from HDFS and MapReduce version 1 (MRv1) to one running HDFS and MapReduce version 2 (MRv2) on YARN. You want to set and enforce version 1 (MRv1) to one running HDFS and MapReduce version 2 (MRv2) on YARN. You want to set and enforce a block size of 128MB for all new files written to the cluster after upgrade. What should you do?

• A. You cannot enforce this, since client code can always override this value
• B. Set dfs.block.size to 128M on all the worker nodes, on all client machines, and on the NameNode, and set the parameter to final
• C. Set dfs.block.size to 128 M on all the worker nodes and client machines, and set the parameter to fina
• D. You do not need to set this value on the NameNode
• E. Set dfs.block.size to 134217728 on all the worker nodes, on all client machines, and on the NameNode, and set the parameter to final
• F. Set dfs.block.size to 134217728 on all the worker nodes and client machines, and set the parameter to fina
• G. You do not need to set this value on the NameNode

Answer: C

NEW QUESTION 5
Which scheduler would you deploy to ensure that your cluster allows short jobs to finish within a reasonable time without starting long-running jobs?

• A. Complexity Fair Scheduler (CFS)
• B. Capacity Scheduler
• C. Fair Scheduler
• D. FIFO Scheduler

Answer: C

Explanation: Reference:http://hadoop.apache.org/docs/r1.2.1/fair_scheduler.html

NEW QUESTION 6
A slave node in your cluster has 4 TB hard drives installed (4 x 2TB). The DataNode is configured to store HDFS blocks on all disks. You set the value of the dfs.datanode.du.reserved parameter to 100 GB. How does this alter HDFS block storage?

• A. 25GB on each hard drive may not be used to store HDFS blocks
• B. 100GB on each hard drive may not be used to store HDFS blocks
• C. All hard drives may be used to store HDFS blocks as long as at least 100 GB in total is available on the node
• D. A maximum if 100 GB on each hard drive may be used to store HDFS blocks

Answer: B

NEW QUESTION 7
You are migrating a cluster from MApReduce version 1 (MRv1) to MapReduce version 2 (MRv2) on YARN. You want to maintain your MRv1 TaskTracker slot capacities when you migrate. What should you do/

• A. Configure yarn.applicationmaster.resource.memory-mb and yarn.applicationmaster.resource.cpu-vcores so that ApplicationMaster container allocations match the capacity you require.
• B. You don’t need to configure or balance these properties in YARN as YARN dynamically balances resource management capabilities on your cluster
• C. Configure mapred.tasktracker.map.tasks.maximum and mapred.tasktracker.reduce.tasks.maximum ub yarn-site.xml to match your cluster’s capacity set by the yarn-scheduler.minimum-allocation
• D. Configure yarn.nodemanager.resource.memory-mb and yarn.nodemanager.resource.cpu-vcores to match the capacity you require under YARN for each NodeManager

Answer: D

NEW QUESTION 8
You suspect that your NameNode is incorrectly configured, and is swapping memory to disk. Which Linux commands help you to identify whether swapping is occurring?(Select all that apply)

• A. free
• B. df
• C. memcat
• D. top
• E. jps
• F. vmstat
• G. swapinfo

Answer: ADF

Explanation: Reference:http://www.cyberciti.biz/faq/linux-check-swap-usage-command/

NEW QUESTION 9
Given:

You want to clean up this list by removing jobs where the State is KILLED. What command you enter?

• A. Yarn application –refreshJobHistory
• B. Yarn application –kill application_1374638600275_0109
• C. Yarn rmadmin –refreshQueue
• D. Yarn rmadmin –kill application_1374638600275_0109

Answer: B

Explanation: Reference:http://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.1-latest/bk_using-apache-hadoop/content/common_mrv2_commands.html

NEW QUESTION 10
Your cluster has the following characteristics:
✑ A rack aware topology is configured and on
✑ Replication is set to 3
✑ Cluster block size is set to 64MB
Which describes the file read process when a client application connects into the cluster and requests a 50MB file?

• A. The client queries the NameNode for the locations of the block, and reads all three copie
• B. The first copy to complete transfer to the client is the one the client reads as part of hadoop’s speculative execution framework.
• C. The client queries the NameNode for the locations of the block, and reads from the first location in the list it receives.
• D. The client queries the NameNode for the locations of the block, and reads from a random location in the list it receives to eliminate network I/O loads by balancing which nodes it retrieves data from any given time.
• E. The client queries the NameNode which retrieves the block from the nearest DataNode to the client then passes that block back to the client.

Answer: B

NEW QUESTION 11
You have recently converted your Hadoop cluster from a MapReduce 1 (MRv1) architecture to MapReduce 2 (MRv2) on YARN architecture. Your developers are accustomed to specifying map and reduce tasks (resource allocation) tasks when they run jobs: A developer wants to know how specify to reduce tasks when a specific job runs. Which method should you tell that developers to implement?

• A. MapReduce version 2 (MRv2) on YARN abstracts resource allocation away from the idea of “tasks” into memory and virtual cores, thus eliminating the need for a developer to specify the number of reduce tasks, and indeed preventing the developer from specifying the number of reduce tasks.
• B. In YARN, resource allocations is a function of megabytes of memory in multiples of 1024m
• C. Thus, they should specify the amount of memory resource they need by executing –D mapreduce-reduces.memory-mb-2048
• D. In YARN, the ApplicationMaster is responsible for requesting the resource required for a specific launc
• E. Thus, executing –D yarn.applicationmaster.reduce.tasks=2 will specify that the ApplicationMaster launch two task contains on the worker nodes.
• F. Developers specify reduce tasks in the exact same way for both MapReduce version 1 (MRv1) and MapReduce version 2 (MRv2) on YAR
• G. Thus, executing –D mapreduce.job.reduces-2 will specify reduce tasks.
• H. In YARN, resource allocation is function of virtual cores specified by the ApplicationManager making requests to the NodeManager where a reduce task is handeled by a single container (and thus a single virtual core). Thus, the developer needs to specify the number of virtual cores to the NodeManager by executing –p yarn.nodemanager.cpu-vcores=2

Answer: D

NEW QUESTION 12
Which is the default scheduler in YARN?

• A. YARN doesn’t configure a default scheduler, you must first assign an appropriate scheduler class in yarn-site.xml
• B. Capacity Scheduler
• C. Fair Scheduler
• D. FIFO Scheduler

Answer: B

Explanation: Reference:http://hadoop.apache.org/docs/r2.4.1/hadoop-yarn/hadoop-yarn-site/CapacityScheduler.html

NEW QUESTION 13
Which two are features of Hadoop’s rack topology?(Choose two)

• A. Configuration of rack awareness is accomplished using a configuration fil
• B. You cannot use a rack topology script.
• C. Hadoop gives preference to intra-rack data transfer in order to conserve bandwidth
• D. Rack location is considered in the HDFS block placement policy
• E. HDFS is rack aware but MapReduce daemon are not
• F. Even for small clusters on a single rack, configuring rack awareness will improve performance

Answer: BC

NEW QUESTION 14
Each node in your Hadoop cluster, running YARN, has 64GB memory and 24 cores. Your yarn.site.xml has the following configuration:
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>32768</value>
</property>
<property>
<name>yarn.nodemanager.resource.cpu-vcores</name>
<value>12</value>
</property>
You want YARN to launch no more than 16 containers per node. What should you do?

• A. Modify yarn-site.xml with the following property:<name>yarn.scheduler.minimum-allocation-mb</name><value>2048</value>
• B. Modify yarn-sites.xml with the following property:<name>yarn.scheduler.minimum-allocation-mb</name><value>4096</value>
• C. Modify yarn-site.xml with the following property:<name>yarn.nodemanager.resource.cpu-vccores</name>
• D. No action is needed: YARN’s dynamic resource allocation automatically optimizes the node memory and cores

Answer: A

NEW QUESTION 15
Cluster Summary:
45 files and directories, 12 blocks = 57 total. Heap size is 15.31 MB/193.38MB(7%)

Refer to the above screenshot.
You configure a Hadoop cluster with seven DataNodes and on of your monitoring UIs displays the details shown in the exhibit.
What does the this tell you?

• A. The DataNode JVM on one host is not active
• B. Because your under-replicated blocks count matches the Live Nodes, one node is dead, and your DFS Used % equals 0%, you can’t be certain that your cluster has all the data you’ve written it.
• C. Your cluster has lost all HDFS data which had bocks stored on the dead DatNode
• D. The HDFS cluster is in safe mode

Answer: A

NEW QUESTION 16
You want to understand more about how users browse your public website. For example, you want to know which pages they visit prior to placing an order. You have a server farm of 200 web servers hosting your website. Which is the most efficient process to gather these web server across logs into your Hadoop cluster analysis?

• A. Sample the web server logs web servers and copy them into HDFS using curl
• B. Ingest the server web logs into HDFS using Flume
• C. Channel these clickstreams into Hadoop using Hadoop Streaming
• D. Import all user clicks from your OLTP databases into Hadoop using Sqoop
• E. Write a MapReeeduce job with the web servers for mappers and the Hadoop cluster nodes for reducers

Answer: B

Explanation: Apache Flume is a service for streaming logs into Hadoop.
Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of streaming data into the Hadoop Distributed File System (HDFS). It has a simple and flexible architecture based on streaming data flows; and is robust and fault tolerant with tunable reliability mechanisms for failover and recovery.

NEW QUESTION 17
Which two features does Kerberos security add to a Hadoop cluster?(Choose two)

• A. User authentication on all remote procedure calls (RPCs)
• B. Encryption for data during transfer between the Mappers and Reducers
• C. Encryption for data on disk (“at rest”)
• D. Authentication for user access to the cluster against a central server
• E. Root access to the cluster for users hdfs and mapred but non-root access for clients

Answer: AD